About
7
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Introduction
Hi! I am a Doctoral Researcher at the Max Planck Institute (MPI-DCTS) in Magdeburg, Germany. There, I work in the Computational Methods in Systems and Control Theory (CSC) group with Dr. Lihong Feng and Prof. Peter Benner. My research focus is developing reduced-order modeling techniques for parametric nonlinear dynamical systems by combining concepts from machine learning and computational physics.
Current institution
Additional affiliations
August 2017 - October 2019
May 2014 - July 2014
May 2015 - May 2016
Education
October 2016 - September 2019
July 2011 - May 2015
Publications
Publications (7)
In this paper, force convective flow and heat transfer characteristics past an unconfined blunt headed cylinder has been computed for various ranges of Reynolds and Prandtl numbers. The mathematical model is first validated with the available results from literature and are found to be in good agreement. The boundary layer separation and the local...
Previous works have developed boundary conditions that lead to the $L^2$-boundedness of solutions to the linearised moment equations.
Here we present a spatial discretization that preserves the $L^2$-stability
by recovering integration-by-parts over the discretized domain and by imposing boundary conditions using a simultaneous-approximation-term (...
When repeated evaluations for varying parameter configurations of a high-fidelity physical model are required, surrogate modeling techniques based on model order reduction are desired. In absence of the governing equations describing the dynamics, we need to construct the parametric reduced-order surrogate model in a non-intrusive fashion. In this...
Partial differential equation parameter estimation is a mathematical and computational process used to estimate the unknown parameters in a partial differential equation model from observational data. This paper employs a greedy sampling approach based on the Discrete Empirical Interpolation Method to identify the most informative samples in a data...
In situations where the solution of a high-fidelity dynamical system needs to be evaluated repeatedly, over a vast pool of parametric configurations and in absence of access to the underlying governing equations, data-driven model reduction techniques are preferable. We propose a novel active learning approach to build a parametric data-driven redu...
In this paper, a two-dimensional numerical simulation is carried out to understand the effect of confinement (blockage ratio β) on fluid flow and forced convective heat transfer characteristics past a blunt headed cylinder. Utilizing air as an operating fluid, flow simulations are carried out for wide ranges of blockage ratios ≤ ≤ () β 1 10 1 3 and...
